Senior Research Engineer 106523
Tencent
Senior Research Engineer 106523
Job Description
Senior Research Engineer 106523
📋 Job Overview
The Senior Research Engineer role at Tencent's Technology Engineering Group involves researching and optimizing content generation models for text, images, audio, and 3D models to enhance quality, diversity, controllability, and efficiency. The position focuses on improving user experience and production effectiveness through algorithm training, optimization in areas like image generation and multi-modal large models, and addressing real-world business challenges. Responsibilities include prompt optimization, model R&D, adapter development, performance acceleration, and industrial deployment of multimodal generative models.
📍 Location: CapitaSky, Singapore
🏢 Business Unit: TEG
📄 Full Description
Business Unit
Technology Engineering Group (TEG) is responsible for supporting the company and its business groups on technology and operational platforms, as well as the construction and operation of R&D management and data centers, TEG provides users with a full range of customer services. As the operator of the largest networking, devices, and data center in Asia,TEG also leads the Tencent Technology Committee in strengthening infrastructure R&D through internal and distributed open source collaboration, constructing new platforms and supporting business innovation.
What the Role Entails
Research and optimize content generation models (text, image, audio, 3D models, etc.) to address challenges such as generation quality, diversity, controllability, and efficiency.
Aim to improve user experience and production effectiveness, and support the productization of algorithms.
Conduct algorithm training and optimization in areas such as image generation, multi-modal large models, and few-shot learning.
Based on inhouse products and business needs, improve the performance and experience of AI painting, text generation, and video generation through: Prompt optimization / Generation model R&D / Adapter development / Performance acceleration which also includes resolving algorithm bottlenecks when applying models in real business scenarios.
Address the industrial deployment of multimodal generative models and actively explore model design and optimization in an R&D context
Who We Look For
PhD (preferably fulltime) in Computer Science, Artificial Intelligence, Mathematics, or related fields.
Solid foundation in computer vision or machine learning algorithms; candidates with publications in top conferences or journals are preferred.
Proficient in machine learning and deep learning fundamentals, and familiar with mainstream AIGC frameworks, including GAN, VAE, VQGAN, Diffusion models, etc.
Familiar with generation model extensions such as ControlNet, LoRA, and Text Inversion.
Familiar with multi-modal models like CLIP, ERNIE-ViL, and other transformer-based cross-modal representation models. Hands-on experience in NLP, multi-modal learning, or AI-generated content is a strong plus.
Strong learning ability, clear logical thinking, excellent communication skills, and a high level of curiosity.
Good teamwork and interpersonal communication skills.
Fluency in both English and Mandarin to deal with international stakeholders and stakeholders who are based in HQ
Equal Employment Opportunity at Tencent
As an equal opportunity employer, we firmly believe that diverse voices fuel our innovation and allow us to better serve our users and the community. We foster an environment where every employee of Tencent feels supported and inspired to achieve individual and common goals.
Work Location: Singapore-CapitaSky
Technology Engineering Group (TEG) is responsible for supporting the company and its business groups on technology and operational platforms, as well as the construction and operation of R&D management and data centers, TEG provides users with a full range of customer services. As the operator of the largest networking, devices, and data center in Asia,TEG also leads the Tencent Technology Committee in strengthening infrastructure R&D through internal and distributed open source collaboration, constructing new platforms and supporting business innovation.
What the Role Entails
Research and optimize content generation models (text, image, audio, 3D models, etc.) to address challenges such as generation quality, diversity, controllability, and efficiency.
Aim to improve user experience and production effectiveness, and support the productization of algorithms.
Conduct algorithm training and optimization in areas such as image generation, multi-modal large models, and few-shot learning.
Based on inhouse products and business needs, improve the performance and experience of AI painting, text generation, and video generation through: Prompt optimization / Generation model R&D / Adapter development / Performance acceleration which also includes resolving algorithm bottlenecks when applying models in real business scenarios.
Address the industrial deployment of multimodal generative models and actively explore model design and optimization in an R&D context
Who We Look For
PhD (preferably fulltime) in Computer Science, Artificial Intelligence, Mathematics, or related fields.
Solid foundation in computer vision or machine learning algorithms; candidates with publications in top conferences or journals are preferred.
Proficient in machine learning and deep learning fundamentals, and familiar with mainstream AIGC frameworks, including GAN, VAE, VQGAN, Diffusion models, etc.
Familiar with generation model extensions such as ControlNet, LoRA, and Text Inversion.
Familiar with multi-modal models like CLIP, ERNIE-ViL, and other transformer-based cross-modal representation models. Hands-on experience in NLP, multi-modal learning, or AI-generated content is a strong plus.
Strong learning ability, clear logical thinking, excellent communication skills, and a high level of curiosity.
Good teamwork and interpersonal communication skills.
Fluency in both English and Mandarin to deal with international stakeholders and stakeholders who are based in HQ
Equal Employment Opportunity at Tencent
As an equal opportunity employer, we firmly believe that diverse voices fuel our innovation and allow us to better serve our users and the community. We foster an environment where every employee of Tencent feels supported and inspired to achieve individual and common goals.
Work Location: Singapore-CapitaSky
🎯 Key Responsibilities
- Research and optimize content generation models (text, image, audio, 3D models, etc.) to address challenges such as generation quality, diversity, controllability, and efficiency
- Aim to improve user experience and production effectiveness, and support the productization of algorithms
- Conduct algorithm training and optimization in areas such as image generation, multi-modal large models, and few-shot learning
- Based on inhouse products and business needs, improve the performance and experience of AI painting, text generation, and video generation through: Prompt optimization / Generation model R&D / Adapter development / Performance acceleration which also includes resolving algorithm bottlenecks when applying models in real business scenarios
- Address the industrial deployment of multimodal generative models and actively explore model design and optimization in an R&D context
✅ Required Qualifications
- PhD (preferably fulltime) in Computer Science, Artificial Intelligence, Mathematics, or related fields
- Solid foundation in computer vision or machine learning algorithms
- Proficient in machine learning and deep learning fundamentals
- Familiar with mainstream AIGC frameworks, including GAN, VAE, VQGAN, Diffusion models, etc.
- Familiar with generation model extensions such as ControlNet, LoRA, and Text Inversion
- Familiar with multi-modal models like CLIP, ERNIE-ViL, and other transformer-based cross-modal representation models
- Strong learning ability, clear logical thinking, excellent communication skills, and a high level of curiosity
- Good teamwork and interpersonal communication skills
- Fluency in both English and Mandarin to deal with international stakeholders and stakeholders who are based in HQ
⭐ Preferred Qualifications
- Candidates with publications in top conferences or journals
- Hands-on experience in NLP, multi-modal learning, or AI-generated content
🛠️ Required Skills
- Solid foundation in computer vision or machine learning algorithms
- Proficiency in machine learning and deep learning fundamentals
- Familiarity with mainstream AIGC frameworks (GAN, VAE, VQGAN, Diffusion models)
- Knowledge of generation model extensions (ControlNet, LoRA, Text Inversion)
- Familiarity with multi-modal models (CLIP, ERNIE-ViL, transformer-based cross-modal representation models)
- Hands-on experience in NLP, multi-modal learning, or AI-generated content (preferred)
- Strong learning ability and clear logical thinking
- Excellent communication skills
- High level of curiosity
- Good teamwork and interpersonal communication skills
- Fluency in English and Mandarin
🎁 Benefits
- Equal Employment Opportunity
- Diverse and inclusive work environment that fosters innovation and supports individual and common goals
- Work Location: Singapore-CapitaSky
Locations
- CapitaSky, Singapore
Salary
Estimated Salary Rangemedium confidence
180,000 - 280,000 SGD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Solid foundation in computer vision or machine learning algorithmsintermediate
- Proficiency in machine learning and deep learning fundamentalsintermediate
- Familiarity with mainstream AIGC frameworks (GAN, VAE, VQGAN, Diffusion models)intermediate
- Knowledge of generation model extensions (ControlNet, LoRA, Text Inversion)intermediate
- Familiarity with multi-modal models (CLIP, ERNIE-ViL, transformer-based cross-modal representation models)intermediate
- Hands-on experience in NLP, multi-modal learning, or AI-generated content (preferred)intermediate
- Strong learning ability and clear logical thinkingintermediate
- Excellent communication skillsintermediate
- High level of curiosityintermediate
- Good teamwork and interpersonal communication skillsintermediate
- Fluency in English and Mandarinintermediate
Required Qualifications
- PhD (preferably fulltime) in Computer Science, Artificial Intelligence, Mathematics, or related fields (experience)
- Solid foundation in computer vision or machine learning algorithms (experience)
- Proficient in machine learning and deep learning fundamentals (experience)
- Familiar with mainstream AIGC frameworks, including GAN, VAE, VQGAN, Diffusion models, etc. (experience)
- Familiar with generation model extensions such as ControlNet, LoRA, and Text Inversion (experience)
- Familiar with multi-modal models like CLIP, ERNIE-ViL, and other transformer-based cross-modal representation models (experience)
- Strong learning ability, clear logical thinking, excellent communication skills, and a high level of curiosity (experience)
- Good teamwork and interpersonal communication skills (experience)
- Fluency in both English and Mandarin to deal with international stakeholders and stakeholders who are based in HQ (experience)
Preferred Qualifications
- Candidates with publications in top conferences or journals (experience)
- Hands-on experience in NLP, multi-modal learning, or AI-generated content (experience)
Responsibilities
- Research and optimize content generation models (text, image, audio, 3D models, etc.) to address challenges such as generation quality, diversity, controllability, and efficiency
- Aim to improve user experience and production effectiveness, and support the productization of algorithms
- Conduct algorithm training and optimization in areas such as image generation, multi-modal large models, and few-shot learning
- Based on inhouse products and business needs, improve the performance and experience of AI painting, text generation, and video generation through: Prompt optimization / Generation model R&D / Adapter development / Performance acceleration which also includes resolving algorithm bottlenecks when applying models in real business scenarios
- Address the industrial deployment of multimodal generative models and actively explore model design and optimization in an R&D context
Benefits
- general: Equal Employment Opportunity
- general: Diverse and inclusive work environment that fosters innovation and supports individual and common goals
- general: Work Location: Singapore-CapitaSky
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Senior Research Engineer 106523
Tencent
Senior Research Engineer 106523
Job Description
Senior Research Engineer 106523
📋 Job Overview
The Senior Research Engineer role at Tencent's Technology Engineering Group involves researching and optimizing content generation models for text, images, audio, and 3D models to enhance quality, diversity, controllability, and efficiency. The position focuses on improving user experience and production effectiveness through algorithm training, optimization in areas like image generation and multi-modal large models, and addressing real-world business challenges. Responsibilities include prompt optimization, model R&D, adapter development, performance acceleration, and industrial deployment of multimodal generative models.
📍 Location: CapitaSky, Singapore
🏢 Business Unit: TEG
📄 Full Description
Business Unit
Technology Engineering Group (TEG) is responsible for supporting the company and its business groups on technology and operational platforms, as well as the construction and operation of R&D management and data centers, TEG provides users with a full range of customer services. As the operator of the largest networking, devices, and data center in Asia,TEG also leads the Tencent Technology Committee in strengthening infrastructure R&D through internal and distributed open source collaboration, constructing new platforms and supporting business innovation.
What the Role Entails
Research and optimize content generation models (text, image, audio, 3D models, etc.) to address challenges such as generation quality, diversity, controllability, and efficiency.
Aim to improve user experience and production effectiveness, and support the productization of algorithms.
Conduct algorithm training and optimization in areas such as image generation, multi-modal large models, and few-shot learning.
Based on inhouse products and business needs, improve the performance and experience of AI painting, text generation, and video generation through: Prompt optimization / Generation model R&D / Adapter development / Performance acceleration which also includes resolving algorithm bottlenecks when applying models in real business scenarios.
Address the industrial deployment of multimodal generative models and actively explore model design and optimization in an R&D context
Who We Look For
PhD (preferably fulltime) in Computer Science, Artificial Intelligence, Mathematics, or related fields.
Solid foundation in computer vision or machine learning algorithms; candidates with publications in top conferences or journals are preferred.
Proficient in machine learning and deep learning fundamentals, and familiar with mainstream AIGC frameworks, including GAN, VAE, VQGAN, Diffusion models, etc.
Familiar with generation model extensions such as ControlNet, LoRA, and Text Inversion.
Familiar with multi-modal models like CLIP, ERNIE-ViL, and other transformer-based cross-modal representation models. Hands-on experience in NLP, multi-modal learning, or AI-generated content is a strong plus.
Strong learning ability, clear logical thinking, excellent communication skills, and a high level of curiosity.
Good teamwork and interpersonal communication skills.
Fluency in both English and Mandarin to deal with international stakeholders and stakeholders who are based in HQ
Equal Employment Opportunity at Tencent
As an equal opportunity employer, we firmly believe that diverse voices fuel our innovation and allow us to better serve our users and the community. We foster an environment where every employee of Tencent feels supported and inspired to achieve individual and common goals.
Work Location: Singapore-CapitaSky
Technology Engineering Group (TEG) is responsible for supporting the company and its business groups on technology and operational platforms, as well as the construction and operation of R&D management and data centers, TEG provides users with a full range of customer services. As the operator of the largest networking, devices, and data center in Asia,TEG also leads the Tencent Technology Committee in strengthening infrastructure R&D through internal and distributed open source collaboration, constructing new platforms and supporting business innovation.
What the Role Entails
Research and optimize content generation models (text, image, audio, 3D models, etc.) to address challenges such as generation quality, diversity, controllability, and efficiency.
Aim to improve user experience and production effectiveness, and support the productization of algorithms.
Conduct algorithm training and optimization in areas such as image generation, multi-modal large models, and few-shot learning.
Based on inhouse products and business needs, improve the performance and experience of AI painting, text generation, and video generation through: Prompt optimization / Generation model R&D / Adapter development / Performance acceleration which also includes resolving algorithm bottlenecks when applying models in real business scenarios.
Address the industrial deployment of multimodal generative models and actively explore model design and optimization in an R&D context
Who We Look For
PhD (preferably fulltime) in Computer Science, Artificial Intelligence, Mathematics, or related fields.
Solid foundation in computer vision or machine learning algorithms; candidates with publications in top conferences or journals are preferred.
Proficient in machine learning and deep learning fundamentals, and familiar with mainstream AIGC frameworks, including GAN, VAE, VQGAN, Diffusion models, etc.
Familiar with generation model extensions such as ControlNet, LoRA, and Text Inversion.
Familiar with multi-modal models like CLIP, ERNIE-ViL, and other transformer-based cross-modal representation models. Hands-on experience in NLP, multi-modal learning, or AI-generated content is a strong plus.
Strong learning ability, clear logical thinking, excellent communication skills, and a high level of curiosity.
Good teamwork and interpersonal communication skills.
Fluency in both English and Mandarin to deal with international stakeholders and stakeholders who are based in HQ
Equal Employment Opportunity at Tencent
As an equal opportunity employer, we firmly believe that diverse voices fuel our innovation and allow us to better serve our users and the community. We foster an environment where every employee of Tencent feels supported and inspired to achieve individual and common goals.
Work Location: Singapore-CapitaSky
🎯 Key Responsibilities
- Research and optimize content generation models (text, image, audio, 3D models, etc.) to address challenges such as generation quality, diversity, controllability, and efficiency
- Aim to improve user experience and production effectiveness, and support the productization of algorithms
- Conduct algorithm training and optimization in areas such as image generation, multi-modal large models, and few-shot learning
- Based on inhouse products and business needs, improve the performance and experience of AI painting, text generation, and video generation through: Prompt optimization / Generation model R&D / Adapter development / Performance acceleration which also includes resolving algorithm bottlenecks when applying models in real business scenarios
- Address the industrial deployment of multimodal generative models and actively explore model design and optimization in an R&D context
✅ Required Qualifications
- PhD (preferably fulltime) in Computer Science, Artificial Intelligence, Mathematics, or related fields
- Solid foundation in computer vision or machine learning algorithms
- Proficient in machine learning and deep learning fundamentals
- Familiar with mainstream AIGC frameworks, including GAN, VAE, VQGAN, Diffusion models, etc.
- Familiar with generation model extensions such as ControlNet, LoRA, and Text Inversion
- Familiar with multi-modal models like CLIP, ERNIE-ViL, and other transformer-based cross-modal representation models
- Strong learning ability, clear logical thinking, excellent communication skills, and a high level of curiosity
- Good teamwork and interpersonal communication skills
- Fluency in both English and Mandarin to deal with international stakeholders and stakeholders who are based in HQ
⭐ Preferred Qualifications
- Candidates with publications in top conferences or journals
- Hands-on experience in NLP, multi-modal learning, or AI-generated content
🛠️ Required Skills
- Solid foundation in computer vision or machine learning algorithms
- Proficiency in machine learning and deep learning fundamentals
- Familiarity with mainstream AIGC frameworks (GAN, VAE, VQGAN, Diffusion models)
- Knowledge of generation model extensions (ControlNet, LoRA, Text Inversion)
- Familiarity with multi-modal models (CLIP, ERNIE-ViL, transformer-based cross-modal representation models)
- Hands-on experience in NLP, multi-modal learning, or AI-generated content (preferred)
- Strong learning ability and clear logical thinking
- Excellent communication skills
- High level of curiosity
- Good teamwork and interpersonal communication skills
- Fluency in English and Mandarin
🎁 Benefits
- Equal Employment Opportunity
- Diverse and inclusive work environment that fosters innovation and supports individual and common goals
- Work Location: Singapore-CapitaSky
Locations
- CapitaSky, Singapore
Salary
Estimated Salary Rangemedium confidence
180,000 - 280,000 SGD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Solid foundation in computer vision or machine learning algorithmsintermediate
- Proficiency in machine learning and deep learning fundamentalsintermediate
- Familiarity with mainstream AIGC frameworks (GAN, VAE, VQGAN, Diffusion models)intermediate
- Knowledge of generation model extensions (ControlNet, LoRA, Text Inversion)intermediate
- Familiarity with multi-modal models (CLIP, ERNIE-ViL, transformer-based cross-modal representation models)intermediate
- Hands-on experience in NLP, multi-modal learning, or AI-generated content (preferred)intermediate
- Strong learning ability and clear logical thinkingintermediate
- Excellent communication skillsintermediate
- High level of curiosityintermediate
- Good teamwork and interpersonal communication skillsintermediate
- Fluency in English and Mandarinintermediate
Required Qualifications
- PhD (preferably fulltime) in Computer Science, Artificial Intelligence, Mathematics, or related fields (experience)
- Solid foundation in computer vision or machine learning algorithms (experience)
- Proficient in machine learning and deep learning fundamentals (experience)
- Familiar with mainstream AIGC frameworks, including GAN, VAE, VQGAN, Diffusion models, etc. (experience)
- Familiar with generation model extensions such as ControlNet, LoRA, and Text Inversion (experience)
- Familiar with multi-modal models like CLIP, ERNIE-ViL, and other transformer-based cross-modal representation models (experience)
- Strong learning ability, clear logical thinking, excellent communication skills, and a high level of curiosity (experience)
- Good teamwork and interpersonal communication skills (experience)
- Fluency in both English and Mandarin to deal with international stakeholders and stakeholders who are based in HQ (experience)
Preferred Qualifications
- Candidates with publications in top conferences or journals (experience)
- Hands-on experience in NLP, multi-modal learning, or AI-generated content (experience)
Responsibilities
- Research and optimize content generation models (text, image, audio, 3D models, etc.) to address challenges such as generation quality, diversity, controllability, and efficiency
- Aim to improve user experience and production effectiveness, and support the productization of algorithms
- Conduct algorithm training and optimization in areas such as image generation, multi-modal large models, and few-shot learning
- Based on inhouse products and business needs, improve the performance and experience of AI painting, text generation, and video generation through: Prompt optimization / Generation model R&D / Adapter development / Performance acceleration which also includes resolving algorithm bottlenecks when applying models in real business scenarios
- Address the industrial deployment of multimodal generative models and actively explore model design and optimization in an R&D context
Benefits
- general: Equal Employment Opportunity
- general: Diverse and inclusive work environment that fosters innovation and supports individual and common goals
- general: Work Location: Singapore-CapitaSky
Tags & Categories
Answer 10 quick questions to check your fit for Senior Research Engineer 106523 @ Tencent.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs